Well, traditional methods no longer suffice. The practice of simply engaging with the customer at the time of renewal is insufficient. And insurers often:

Struggle to access the appropriate data needed to drive retention rates upward.
Lack the analytics to empower frontline personnel to make optimal retention decisions.
Fail to measure the effectiveness of their retention actions and processes – and adjust course.

That need not be the case. Insurers can leverage new data sources and predictive analytics to decrease churn and discover opportunities for cross-sell and up-sell. To improve your customer retention, we recommend a four-step process:

Leverage insights from internal and external data. Insurers should start by ensuring that they are maximizing the internal data available to them. Start with core and adjacent systems such as, claims, underwriting, policy, billing, CRM, and other customer interaction sources. Supplement this with external third-party data. There is a wealth of data readily available now that was not available just a few short years ago. Look to data sources for consumer purchase behavior, spending habits, prior insurance or traffic violations — and then go a step further with firmographic information. Upping your data game will enhance your overall customer intelligence, predictive capabilities, and ultimately your retention.

Implement a predictive model. The next step is to leverage the data in a predictive model. There are a range of models available on the market – and some larger insurers build their own models. When selecting a modeling tool, be sure that it can support machine learning languages such as R and Python. The modeling tool should also be able to 'operationalize' the model results into the underwriting processes thereby creating a system of insight.

Leverage analytics to take customer-specific retention actions. Once the modeling solution is put into production, frontline personnel can take customer-specific retention actions (Figure 1), that properly balance retention likelihood and customer profitability. These actions will also help improve customer satisfaction as the insurer is engaged with the customer throughout the policy lifecycle and not just at renewal.

Figure 1: Customer specific retention actions(Credit: Guidewire)

Measure business impact and adjust your model, as necessary. Best-in-class practices call for insurers to continuously monitor and improve their predictive models and processes with real-time audits. Best-in-class solutions will monitor key metrics in real-time and offer the capability to compare model performance prior to rollout with A/B testing.

Satyen Paneri of Guidewire. (Credit: Jay Kelly/Studio J Photo)

Special Reports /

Predictive analytics can dramatically improve retention, prime growth

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